VP, Data Science

ABOUT THIS POSITION

Waystar is a market-leading provider of cloud-based healthcare payments software. Our mission‑critical platform simplifies the complex revenue cycle for providers, enabling them to get paid faster and more accurately, and focus on patient care. We process billions of transactions annually, leveraging a massive dataset of claims, remittances, and patient data to drive outcomes. With Waystar Altitude

AI™, we are at the forefront of applying AI, generative AI, and advanced automation to transform healthcare finance, reduce administrative burden, and achieve peak financial performance for our clients.

As the VP of Data Science, you will be a strategic and technical leader reporting directly to the SVP of Data Science + Analytics. Your primary responsibility will be to establish and execute the data science strategy that underpins the evolution of the Waystar Altitude

AI ™ platform. This role demands a visionary who can lead a world‑class team, driving innovation to solve the most critical challenges in healthcare revenue cycle management (RCM)—from preventing denials and optimizing prior authorizations to delivering transparent patient financial experiences. You must possess deep technical expertise in machine learning, including foundation models, and have consistently delivered production‑grade, highly available solutions that yield quantifiable improvements in customer outcomes in complex, regulated environments.

• Develop and champion a comprehensive data science and ML strategy that directly translates into new product capabilities and significant business value for Waystar and its clients. Focus on using data to predict, prevent, and automate RCM workflows.

• Establish and steward a portfolio of model types (e.g., classification, regression, ranking, forecasting, NLP/LLMs, anomaly detection) that address both clinical and financial objectives.

• Integrate heterogeneous model outputs (clinical insights, operational predictions, financial risk scores) into an integrated, governed enterprise data set that supports analytics, product experiences, and downstream decisioning.

• Collaborate closely with product, engineering, and commercial leaders to embed data science and ML into core platform offerings, ensuring technical initiatives align with market needs and HIPAA/security compliance.

• Spearhead the research and deployment of cutting‑edge AI and Generative AI solutions (e.g., using LLMs for policy document interpretation, predictive modeling for claim denial rates, intelligent task prioritization) to create differentiated, proprietary technology.

• Act as a thought leader with analysts, customers, and prospects; communicate our approach, differentiation, and evidence of impact.

• Attract, mentor, and scale a high‑performing, geographically distributed team of Data Scientists and Machine Learning Engineers, fostering a culture of technical excellence, accountability, and continuous learning.

• Define and enforce best practices for the entire machine learning lifecycle in a regulated environment, including robust model governance, versioning, continuous monitoring, and drift detection to ensure accuracy and compliance of all production models.

• Ensure the team operates with the highest standards of data governance, privacy (HIPAA), and algorithmic fairness, specifically addressing bias and transparency in models impacting provider finances and patient care.

• Act as the ultimate technical authority on machine learning principles, statistical rigor, and large‑scale data analysis within the company. Provide hands‑on guidance on complex projects involving unstructured healthcare data.

• Demonstrated experience and deep theoretical understanding of Foundation Models (e.g., LLMs, VLMs), including model selection, fine‑tuning techniques (e.g., LoRA, QLoRA), Retrieval‑Augmented Generation (RAG) implementation, and prompt engineering for generating accurate, context‑aware outputs in a healthcare setting (e.g., summarizing policy documents, drafting claim…